COURSE UNIT TITLE

: SPATIAL STATISTICS IN GIS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
GIS 6026 SPATIAL STATISTICS IN GIS ELECTIVE 2 1 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR KEMAL MERT ÇUBUKÇU

Offered to

Geographical Information Systems (Non-Thesis) (English)
GEOGRAPHICAL INFORMATION SYSTEMS (ENGLISH)
GEOGRAPHIC INFORMATION SYSTEMS (ENGLISH)
GEOGRAPHICAL INFORMATION SYSTEMS - NON THESIS (EVENING PROGRAM) (ENGLISH)

Course Objective

This course provides an introduction to the spatial statistics based on point data. Prior to the introduction to methods regarding to spatial statistics, basic concepts and methods on (non-spatial) statistics are covered. Conditions of use, assumptions, and accuracy of results are examined for each spatial and non-spatial method. The emphasis is on developing analytical skills with practical applications using statistical software and GIS. The course material is cumulative.

Learning Outcomes of the Course Unit

1   Recognize the basic concepts of spatial statistics, as well as the classical statistical techniques
2   Differentiate the basictechniques in spatial statistics
3   Solve numerical examples pertaining to the subjects covered in the class
4   Use the basic techniques in spatial statistics to solve problems pertaining to urban planning and urban geography

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Basic Concepts of Statistics: Population Sample Scale Frequency Distribution Confidence Level Outliers and Box-Plots Probability and Random Variables
2 Measures of Central Tendency (non-spatial): Mean Weighted Mean Mean for Classified Data Median Mode Hands-on Exercises
3 Measures of Dispersion (non-spatial): Minimum, Maximum and Range Quartiles and Percentiles Mean Deviation Variance and Standard Deviation Variance and Standard Deviation for Classified Data Variance Coefficient Skewness Kurtosis Hands-on Exercises
4 Relation Between Two Variables: Nominal Scale Phi Coefficient Chi-square Test
5 Relation Between Two Variables: Ordinal Scale Spearman s Rank Correlation Coefficient Kendall s Tau Statistics Interval and Ratio Scales Pearson s Correlation Coefficient
6 Mid-term Examination
7 Comparison of Two or More Samples: Nominal Scale Chi-square Test, 2x2 Tables Chi-square Test, ixj Tables Ordinal Scale Mann-Whitney U-Test Kruskal-Wallis H-Test
8 Comparison of Two or More Samples Interval and Ratio Scales Student s t-Test ANOVA Test Kolmogorov-Simirnov Test
9 Measures of Central Tendency for Point Data (spatial): Mean Center Weighted Mean Center Median Center
10 Mid-term Examination
11 Measures of Dispersion for Point Data (spatial) Standard Deviational Ellipse
12 Measures of Dispersion for Point Data (spatial) Weighted Standard Deviational Ellipse
13 Measures of Relation for Point Data (spatial) Geary s Ratio
14 Measures of Relation for Point Data (spatial) Moran s I Index

Recomended or Required Reading

Wong W.S.W. and Lee J. (2005) Statistical Analysis of Geografhic Information with ArcView GIS and ArcGIS, John Wiley and Sons, Inc.
Stillwell, J., Clarke, G. (Eds.) (2004) Applied GIS and Spatial Analysis, John Wiley & Sons Inc.
Ebdon, D. (1977) Statistics in Geography; Basil Blackwell.
Clark, W.A.V. & Hosking, P.L. (1986) Statistical Methods for Geographers, John Wiley & Sons,

Planned Learning Activities and Teaching Methods

Lectures, theoretical presentations and solved examples.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.50 + FIN * 0.50
4 RST RESIT
5 FCGR FINAL COURSE GRADE MTE * 0.50 + RST * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

Two mid-term examinations and one finel examination.

Language of Instruction

English

Course Policies and Rules

1. Attendance is required.
2. Plagiarism and all other means of cheating are strictly prohibited.

Contact Details for the Lecturer(s)

Dokuz Eylul University, Tinaztepe Campus
School of Architecture
Department of City and Regional Planning
Room #109
Buca/IZMIR 35160
TURKEY
mert.cubukcu@deu.edu.tr
http://kisi.deu.edu.tr/mert.cubukcu

Office Hours

Thursdays, 10:30-12:30

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 2 24
Hands-on Exercises (Computer Lab) 12 1 12
Preparation for Mid-term Exam 2 25 50
Preparation forFinal Exam 1 25 25
Preparation before/after weekly lectures 12 6 72
Mid-Term Examination 2 3 6
Final Examination 1 3 3
TOTAL WORKLOAD (hours) 192

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.131522514223
LO.254315242214
LO.315153112355
LO.441241231225

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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